policy-enforcement

Authority control plane for autonomous work. EMILIA Gate enforces finite customer-owned mandates at protected executor boundaries; the open protocol keeps evidence verifiable.

Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, audit trails. Works with LangChain, CrewAI, MCP.

A cloud native Identity Aware Proxy and Access Control Decision service

Govern consequential AI agent actions in Docker with deterministic policy, human approval, and signed Decision Dossiers.

The open standard for runtime agent control — declarative hooks, policy enforcement, and observability across AI agent frameworks.

The curated list of tools, standards, and resources for governing AI agents in production: policy enforcement, audit trails, EU AI Act compliance, MCP and Claude Code security.

Data policy IN, dynamic view OUT: PACE is the Policy As Code Engine. It helps you to programatically create and apply a data policy to a processing platform like Databricks, Snowflake or BigQuery (or plain 'ol Postgres, even!) with definitions imported from Collibra, Datahub, ODD and the like.

Deterministic governance for AI coding agents. Cedar-based policy engine that intercepts every agent action and evaluates it against deterministic rules before execution.

VERITAS OS is an AI agent governance runtime for decision control, policy enforcement, approval workflows, audit trails, and replayable evidence before real-world actions.

Agent Identity Protocol - Zero-trust security layer for AI agents. Policy enforcement proxy for MCP with Human-in-the-Loop approval, DLP scanning, and audit logging.

Deterministic Linux runtime enforcement with eBPF LSM: block file/network operations before syscalls complete.

Encrypted vault, ZK settlement archiving, x402 payment receipts, Agent Passport binding, and Solana anchoring for OpenClaw and agent runtimes. Drop-in stack — compression, privacy, payments, identity.

Open-source runtime security and execution control for autonomous AI agents. ALLOW, BLOCK, ESCALATE at the execution boundary with auditable evidence.

Framework-neutral control contract for AI agents: eight interception points, three verdicts, and a conformance kit.

Authorization infrastructure for AI agents - policy enforcement, signed WASM bundles, per-request user scope, and audit trail for OpenAI Agents, LangChain, Google ADK, and Pydantic AI.

System-level security for LLM agents: fine-grained policy enforcement on tool calls to defend against indirect prompt injection

MCP policy enforcement plane — deterministic policy on every Model Context Protocol call: identity, RFC 8707 audience binding, tool schema digest pinning, full audit trail. Python, self-hosted, MIT.

MIDAS is an open platform for governing execution authority at decision surfaces across agents, AI systems, and enterprise workflows.

A CLI tool for managing GitHub Actions workflows

Deterministic execution authorization for AI agents and automation systems